Share on facebook
Share on twitter
Share on linkedin
Share on email Challenges of Deploying AI Models

by Jos Gheerardyn, CEO & Co-founder at

Background information

It is no longer news that the artificial intelligence summer we’ve been experiencing for quite a while now is here to stay. AI promises considerable benefits for businesses and economies through its contributions to productivity and efficiency. At the same time, the potential challenges to adoption cannot be ignored. In this whitepaper, we focus on these from a model risk perspective. Here we explore the so-called deployment challenge, highlighting the difficulties in terms of HR, technical know-how and infrastructure required to productionize AI applications.

Download now to discover:

  • The main principles related to productionizing AI
  • The maximization of a Model Risk Management Framework in dealing with the complexities of machine learning algorithms; highlighting the key differences compared to the management of more traditional models

“The cornerstone of any model risk management framework is the validation procedure since this guarantees that models are only deployed when certain quality standards are met.” – Jos Gheerardyn

Download the whitepaper here.

Share this Article
Share on facebook
Share on twitter
Share on linkedin
Share on email
Related Insights
Amsterdam Fintech Week
Take a look at our yearly fintech festival, Amsterdam FinTech Week. Go on the dedicated website to check out the 2021 wrap up!
AMLD5 Guide
A source for consulting PSD2 legislation coupled with commentary, tips & tricks, applicability, in collaboration with our member law firms.